Graph-Based Structural Pattern Learning
Final rept. Sep 2001-Mar 2006
TEXAS UNIV AT ARLINGTON
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The main objective of this project was to design, implement and evaluate new methods for performing pattern learning on structured data represented as graphs and evaluate their application to structural, relational databases relevant to the Evidence Assessment, Grouping, Linking and Evaluation EAGLE program. This work builds on existing methods for graph-based knowledge discovery and concept learning implemented in the SUBDUE structural pattern learning system. The graph-based structural pattern learning algorithm was extended to perform structural concept learning and structural, hierarchical conceptual clustering. The resulting system was evaluated using several structural databases, including those with known structural patterns, those of relevance to the target domains of the EAGLE program, and those developed as challenge problems within the EAGLE program.
- Information Science